Ravi Bhavnani, Nina Schlager, Karsten Donnay, Mirko Reul, Laura Schenker, Maxime Staffer and Tirtha Patel. (2023). "Household behavior and vulnerability to acute malnutrition in Kenya." Forthcoming in Humanities and Social Sciences Communications. DOI: 10.1057/s41599-023-01547-8

Data availability statement:
This repository provides the data used in the referred article. The data are provided, wherever applicable in final processed form, original sources for (raw) data are provided in this documentation. Restrictions only apply to the availability of the NDMA household-level data. To safeguard privacy, we provide these data at the ward level, matching the spatial level of aggregation used in this study.

Index of data provided:

1. NDMA (aggregated) malnutrition prevalence rates:
This data draws on detailed household-level records provided by the National Drought Management Authority of Kenya (NDMA). The data provided are aggregated to average malnutrition rates (over 2-mon to 2-year periods, depending on the analysis) and at the ward level. This matches the level of analysis used in the study.

The data are provided in tabular form (.csv) and the naming convention is first region (West Pokot/Turkana), then label (NDMA malnutrition prevalence) and then time period of aggregation (in years or years and months).

List of files:	WestPokot_NDMA_malnutrition_prevalence_2017.csv	WestPokot_NDMA_malnutrition_prevalence_2018.csv
	WestPokot_NDMA_malnutrition_prevalence_2017-2018.csv	WestPokot_NDMA_malnutrition_prevalence_2019_01-02.csv	WestPokot_NDMA_malnutrition_prevalence_2019_01-04.csv	WestPokot_NDMA_malnutrition_prevalence_2019_05-06.csv
	WestPokot_NDMA_malnutrition_prevalence_2019_05-08.csv	WestPokot_NDMA_malnutrition_prevalence_2019_09-10.csv	WestPokot_NDMA_malnutrition_prevalence_2019_09-12.csv	WestPokot_NDMA_malnutrition_prevalence_2020_01-02.csv	WestPokot_NDMA_malnutrition_prevalence_2020_01-04.csv	Turkana_NDMA_malnutrition_prevalence_2017.csv	Turkana_NDMA_malnutrition_prevalence_2018.csv
	Turkana_NDMA_malnutrition_prevalence_2017-2018.csv	Turkana_NDMA_malnutrition_prevalence_2019_01-02.csv	Turkana_NDMA_malnutrition_prevalence_2019_01-04.csv	Turkana_NDMA_malnutrition_prevalence_2019_05-06.csv	Turkana_NDMA_malnutrition_prevalence_2019_05-08.csv	Turkana_NDMA_malnutrition_prevalence_2019_09-10.csv	Turkana_NDMA_malnutrition_prevalence_2019_09-12.csv
	

List of related figures:
	Figure 3. West Pokot: Observed Acute Malnutrition Prevalence vs. Simulation (2017-2018)
	Figure 4. West Pokot: 4-month Leading-Edge Predictions of Acute Malnutrition Prevalence (2019)
	Figure 5. West Pokot: Joint Validity Scale
	Figure 6. Turkana: Observed Acute Malnutrition Prevalence vs. Simulation (2017-2018)
	Figure 7. West Pokot: Counterfactual Scenarios for Select Wards (2020)
	Figure S4: West Pokot: 2-month Leading-Edge Predictions (2019)
	Figure S8: West Pokot: Counterfactual Scenarios for Alternative Wards (2019)
	Figure S5: Turkana: 4-month Leading-Edge Predictions (2019).
	Figure S6: Turkana: 2-month Leading-Edge Predictions (2019).
	Figure S7: Turkana: Joint Validity Scale.


2. Ward level shape files:
We draw on publicly available data from GADM (www.gadm.org) to obtain ward level shape files for Kenya and extract those for the two relevant regions, West Pokot and Turkana. The data are provided as .zip archives that contain all relevant shape file information.

List of files:
	WestPokot_Wards.zip
	Turkana_Wards.zip

List of related figures:
	Figure 1. Map of West Pokot County, Kenya
	Figure 3. West Pokot: Observed Acute Malnutrition Prevalence vs. Simulation (2017-2018)
	Figure 4. West Pokot: 4-month Leading-Edge Predictions of Acute Malnutrition Prevalence (2019)
	Figure 6. Turkana: Observed Acute Malnutrition Prevalence vs. Simulation (2017-2018)
	Figure 7. West Pokot: Counterfactual Scenarios for Select Wards (2020)
	Figure S4: West Pokot: 2-month Leading-Edge Predictions (2019)
	Figure S8: West Pokot: Counterfactual Scenarios for Alternative Wards (2019)
	Figure S5: Turkana: 4-month Leading-Edge Predictions (2019).
	Figure S6: Turkana: 2-month Leading-Edge Predictions (2019).


3. Climate stressor intensity:
These data are based on NASA NDVI measurement. We specifically use the MOD13A3 v006 data available at https://lpdaac.usgs.gov/products/mod13a3v006/ and calculated spatially averaged monthly NDVI indicators for each of the wards in our sample. 

The data are provided in tabular form (.csv) where the column represents a given month of a given year and the line the ward considered. The two files span 2000-2019 (West Pokot) and 2000-2020 (Turkana).

List of files:
	WestPokot_NDVI_2000-2019.csv
	Turkana_NDVI_2000-2020.csv

List of related figures
	Figure S2: West Pokot: Climate stressor intensity (2000–2019).


4. Economic stressor intensity:
We draw on market price data for different basic food items to develop an index for market stressor intensity for West Pokot (2016-2019) and Turkana (2014-2017). These data are hand-coded from the NDMA County Early Warning Bulletins available here: https://www.ndma.go.ke/index.php/resource-center/early-warning-reports.

The data is provided in tabular form (.csv) and it was used to  calculate monthly deviation rates from a three-year average. Each month was then categorized as stressed
or not where stressor intensity is defined as the mean price increase above the long-term average. 

List of files:
	WestPokot_food_prices_2016-2019.csv
	Turkana_food_prices_2014-2017.csv

List of related figures:
	Figure S1: West Pokot: Market stressor intensity (2016–2020)